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Junejo, Muhammad Haleem, Ab Rahman, Ab Al Hadi, Shaikh, Riaz Ahmed 
ORCID: https://orcid.org/0000-0001-6666-0253, Yusof, Kamaludin Mohamad, Kumar, Dileep and Memon, Imran
(2021)
Lightweight trust model with machine learning scheme for secure privacy in VANET.
Procedia Computer Science, 194.
pp. 45-59.
ISSN 1877-0509
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Abstract
A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.
| Item Type: | Article |
|---|---|
| Additional Information: | Publisher Copyright: © 2021 The Authors. Published by Elsevier B.V. |
| Uncontrolled Keywords: | machine learning,trust model,vanet,computer science(all) ,/dk/atira/pure/subjectarea/asjc/1700 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 17 Aug 2022 08:30 |
| Last Modified: | 29 Jun 2023 12:32 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/87351 |
| DOI: | 10.1016/j.procs.2021.10.058 |
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